Fractal analysis for medical image classification and analysis was introduced in cite{Chen1989}. According to the authors, when viewed as an intensity surface, Mandelbrot's fractal theory provides an informative framework for characterizing such a surface. [...]

Convolution is a basic operation in image analysis and the Insight Toolkit provides a well-framed mechanism for such operations (see Chapter 11 of the ITK Software Guide. The classes associated with this contribution are meant to simplify convolution [...]

Although Gabor filtering is quite prevalent in the computer vision community for such tasks as
texture segmentation and motion analysis, such capabilities are conspicuously absent from the
Insight Toolkit. The contribution described in this paper attempts [...]

Texture analysis provides quantitative information describing properties in images such as coarseness and smoothness. Two common quantification schemes are based on co-occurence matrices and run-length matrices. Although the co-occurence measures are [...]

The recent ITKv4 refactoring includes several enhancements to the existing registration framework. These additional transform classes provide access to mappings described by dense displacement fields and their corresponding optimization which complement the [...]

Several algorithms exist for correcting the nonuniform intensity in magnetic resonance images caused by field inhomogeneities. These algorithms constitute important preprocessing steps for subsequent image analysis tasks. One such algorithm, known as [...]

Although the KappaStatisticImageToImageMetric can be used to obtain the Dice metric (or mean overlap), there are other related measurements that are useful for evaluating results derived from various image analysis tasks. These measures include the target [...]

Semi-automatic image segmentation algorithms depend on interaction with the user to accurately define a region of interest within an image. Once such method is a dynamic programming approach called {em Intelligent Scissors} developed by Mortenson and Barret [...]

In an earlier submission, we considered 2-D and 3-D digital binary images topologically characterized by their well-composedness. Well-composed images exhibit important topological and geometrical properties not shared by their ill-composed counterparts. [...]

Certain classes of images find disparate use amongst members of the ITK community for such purposes as visualization, simulation, testing, etc. Currently there exists two derived classes from the ImageSource class used for generating specific images for [...]

Our previous contributions to the ITK community include a generalized B-spline approximation scheme as well as a generalized information-theoretic measure for assessing point-set correspondence known as the Jensen-Havrda-Charvat-Tsallis (JHCT) divergence. In [...]

We provide examples and highlights of Advanced Normalization Tools (ANTS) that address practical problems in real data. A variety of image and point similarity metrics and elastic, diffeomorphic, affine and other variations of transformation models are [...]

Since the 1970's B-splines have evolved to become the {em de facto}
standard for curve and surface representation due to many
of their salient properties. Conventional least-squares
scattered data fitting techniques for B-splines require the inversion [...]

A novel point-set registration algorithm was proposed in [6] based on minimization of the Jensen-Shannon divergence. In this contribution, we generalize this Jensen-Shannon divergence point-set measure framework to the Jensen-Havrda-Charvat-Tsallis [...]

In this submission, we offer the GaussianInterpolationImageFunction which adds to the growing collection of existing interpolation algorithms in ITK for resampling scalar images such as the LinearInterpolateImageFunction, BSplineInterpolateImageFunction, and [...]

We consider 2-D and 3-D digital binary images characterized by their well-composedness. Well-composed images exhibit important topological and geometrical properties not shared by their ill-composed counterparts.
These properties have important [...]

This document describes an ITK implementation of the adaptive patch-based
image denoising algorithm described in cite{Manjon:2010aa}. This offering consists
of the templated class itkPatchBasedDenoisingImageFilter interfaced through
the DenoiseImage program [...]

Topological considerations for segmentation results are important for such applications as proper brain segmentation from digital image data. We present an enhancement of the FastMarchingImageFilter which allows for topologically constrained evolution of the [...]

Fast computation of distance transforms find direct application
in various computer vision problems. Currently there exists
two image filters in the ITK library which can be used to generate
distance maps. Unfortunately, these
filters produce only [...]

Graph-based algorithms have enjoyed renewed interest for solving computer vision problems. These algorithms have been the subject of intense interest and research. In order to maintain the ITK library au courant, we developed a framework for graph-based [...]

Although greyscale intensity values are primarily used in image data visualization oftentimes, due to the requirements of aesthetics (whether they be self-imposed or collaborator-suggested), mapping the greyscale image to a user-defined colormap is desired. [...]

In an earlier Insight Journal article, we introduced an ITK implementation of the adaptive patch-based image denoising algorithm described in [3]. We follow-up up that offering with a generalized non-local, patch-based ITK class framework and a refactored [...]